Triple

T16986011
Position Surface form Disambiguated ID Type / Status
Subject Walter-Ulrich Behrens E412066 entity
Predicate notableConcept P201 FINISHED
Object Behrens–Fisher problem E1244894 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Behrens–Fisher problem | Statement: [Walter-Ulrich Behrens, notableConcept, Behrens–Fisher problem]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Behrens–Fisher problem
Context triple: [Walter-Ulrich Behrens, notableConcept, Behrens–Fisher problem]
  • A. Behrens–Fisher problem chosen
    The Behrens–Fisher problem is a classic statistical inference problem concerning the comparison of means from two normal populations with unknown and unequal variances.
  • B. Hotelling’s T-squared distribution
    Hotelling’s T-squared distribution is a multivariate generalization of Student’s t-distribution used primarily for hypothesis testing and constructing confidence regions for mean vectors in multivariate statistics.
  • C. Student’s t-distribution
    Student’s t-distribution is a continuous probability distribution used primarily to estimate population means and conduct hypothesis tests when sample sizes are small and population variance is unknown.
  • D. Tukey's honestly significant difference test
    Tukey's honestly significant difference test is a statistical post-hoc procedure used to determine which specific group means differ after an ANOVA indicates a significant overall effect.
  • E. Scheffé's method
    Scheffé's method is a conservative multiple comparison procedure in analysis of variance that provides simultaneous confidence intervals for all possible contrasts among group means.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69d886ca8f348190812768ea8d5055ce completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3d18af95c8190a25ef0614e1a17f3 completed April 18, 2026, 6:46 p.m.
NED1 Entity disambiguation (via context triple) batch_6a011b412dd48190862fde6d1656113d completed May 10, 2026, 11:56 p.m.
Created at: April 10, 2026, 5:32 a.m.